We present a preliminary analysis of mobility data collected from an operational GPRS network. The input data are time-series counting the number of mobile stations present in each of 126 sample routing areas at equally spaced instants (5 min) during one full week. The time-series were extracted from packet-level traces captured by passively monitoring a subset of the Gb links of the network of Mobilkom Austria AG & Co KG during October 2004. We apply the principal component analysis (PCA) to this dataset. The PCA offers a simple method for classifying the routing areas into two main groups, residential and business areas, plus a few "atypical" ones. Additionally, we address the problem of robustness of the PCA to temporary local gaps in the input data.
Principal Component Analysis of Mobility Data from an Operational GPRS Network
RICCIATO, FABIO;
2006-01-01
Abstract
We present a preliminary analysis of mobility data collected from an operational GPRS network. The input data are time-series counting the number of mobile stations present in each of 126 sample routing areas at equally spaced instants (5 min) during one full week. The time-series were extracted from packet-level traces captured by passively monitoring a subset of the Gb links of the network of Mobilkom Austria AG & Co KG during October 2004. We apply the principal component analysis (PCA) to this dataset. The PCA offers a simple method for classifying the routing areas into two main groups, residential and business areas, plus a few "atypical" ones. Additionally, we address the problem of robustness of the PCA to temporary local gaps in the input data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.